There is a better way to do this, and it does not require you to build a dozen intermediate columns just to answer a simple question. This user has created a meticulous, multi-step spreadsheet to convert case prices into per-ounce costs, then multiply by a recipe portion, and finally sum those costs across ingredients. The system works, but it is also a monument to the limitations of traditional spreadsheet logic. The user is now trying to automate the process of feeding raw numbers into an LLM, essentially asking the AI to do the math that the spreadsheet is already doing. That is a sign of frustration, not innovation.
What this user has actually discovered is the gap between how we think and how spreadsheets force us to work. When you need to know the cost of 5 ounces of an ingredient, your mind does not want to build a chain of cells dividing by 35.274. Your mind wants to ask: "If 10 KG costs $100, how much is 5 oz?" That is a natural question. The spreadsheet, however, demands you translate that question into a series of intermediate calculations, each with its own cell, its own formula, and its own potential for error. The user has hit the ceiling of what a traditional grid can offer, and they are now looking for a tool that understands the logic behind the numbers, not just the grid they sit in.
This is where AI-native spreadsheets become genuinely transformative. Instead of forcing you to decompose a problem into rigid columns and rows, they let you express your intent in plain language. The user already knows the relationship between their data: price, weight, portion. An intelligent spreadsheet can infer that relationship and compute the answer directly, without you having to manually build the conversion chain. The user's current approach of generating a prompt for an LLM is a clever workaround, but it is still a workaround. The spreadsheet itself should be the one doing the reasoning, not acting as a dumb container for numbers that you then export to another tool.
The practical takeaway is this: if your spreadsheet workflow looks like a recipe with ten steps to get one answer, you are spending your time managing the tool instead of managing your data. The user's system for pricing recipes is functional, but it is also fragile. A single misplaced decimal or a change in case weight breaks the entire chain. The better path is to adopt a tool that lets you describe the relationship between your columns in natural terms, "price per case" and "weight per case", and then ask for the cost per portion directly. The goal is not to eliminate spreadsheets, but to eliminate the busywork they impose. You should be able to go from raw numbers to a finished cost without building a scaffold of intermediate formulas. That is the workflow worth pursuing.